scholarly journals System Dynamics versus Agent-Based Modeling: A Review of Complexity Simulation in Construction Waste Management

2018 ◽  
Vol 10 (7) ◽  
pp. 2484 ◽  
Author(s):  
Zhikun Ding ◽  
Wenyan Gong ◽  
Shenghan Li ◽  
Zezhou Wu
Keyword(s):  
Waste Management ◽  
System Dynamics ◽  
Complex Adaptive System ◽  
Agent Based Modeling ◽  
Effective Management ◽  
Construction Waste ◽  
Agent Based ◽  
Complex Adaptive ◽  
Research Findings ◽  
Novel Model

The environmental impacts caused by construction waste have attracted increasing attention in recent years. The effective management of construction waste is essential in order to reduce negative environmental influences. Construction waste management (CWM) can be viewed as a complex adaptive system, as it involves not only various factors (e.g., social, economic, and environmental), but also different stakeholders (such as developers, contractors, designers, and governmental departments) simultaneously. System dynamics (SD) and agent-based modeling (ABM) are the two most popular approaches to deal with the complexity in CWM systems. However, the two approaches have their own advantages and drawbacks. The aim of this research is to conduct a comprehensive review and develop a novel model for combining the advantages of both SD and ABM. The research findings revealed that two options can be considered when combining SD with ABM; the two options are discussed.

Agent-Based Models

2018 ◽  
Author(s):  
Brenda Heaton ◽  
Abdulrahman El-Sayed ◽  
Sandro Galea
Keyword(s):  
Computational Models ◽  
Autonomous Agents ◽  
Complex Adaptive System ◽  
Agent Based Modeling ◽  
Agent Based Models ◽  
Agent Based ◽  
Or Groups ◽  
Complex Adaptive ◽  
Adaptive Processes ◽  
Neighborhoods And Health

Agent-based modeling is a newer approach to the study of neighborhoods and health. In brief, an agent-based model is one of a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities, such as organizations or groups) with a view to assessing their effects on the system as a whole. Neighborhood characteristics and resources evolve and adapt as the individuals living within them change and vice versa. In this way, neighborhoods reflect a complex adaptive system. In this chapter, we introduce agent-based models as a tool for modeling these interactive and adaptive processes that occur within a system, such as a neighborhood. The chapter provides a basic introduction to this method, drawing on examples from the neighborhoods and health literature.

Multi-Methodology Approach

2021 ◽  
pp. 98-128
Keyword(s):  
System Dynamics ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Multiple Methods ◽  
Soft Systems ◽  
Agent Based ◽  
Event Simulation ◽  
Pluralistic Approach ◽  
The Difference

The pluralistic approach in today's world needs combining multiple methods, whether hard or soft, into a multi-methodology intervention. The methodologies can be combined, sometimes from several different paradigms, including hard and soft, in the form of a multi-methodology so that the hard paradigms are positivistic and see the organizational environment as objective, while the nature of soft paradigms is interpretive. In this chapter, the combination of methodologies has been examined using soft systems methodologies (SSM) and simulation methodologies including discrete event simulation (DES), system dynamics (SD), and agent-based modeling (ABM). Also, using the ontological, epistemological, and methodological assumptions underlying the respective paradigms, the difference between SD, ABM, SSM; a synthesis of SSM and SD generally known as soft system dynamics methodology (SSDM); and a promising integration of SSM and ABM referred to as soft systems agent-based methodology (SSABM) have been proven.

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